Use this guide to help search for and get accurate pricing and turnaround times for small RNA, microRNA (miRNA) sequencing services. The guide includes considerations you should make before starting your small RNA sequencing project.
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All current commercial protocols for preparing microRNA (miRNA) libraries for sequencing take advantage of 5’phosphate and 3’hydroxyl groups on the miRNA, which allow ligases to selectively target and enrich these small RNA species.
The first step of microRNA library preparation involves 3’end ligation using a 5’ adenylated DNA adapter with a blocked 3’end. Using a truncated version of T4 RNA Ligase 2, the ATP-less reaction is driven by the adenylated group on the adapter, resulting in ligation to molecules with a 3’hydroxy group. Other RNA species in the reaction are not ligated together. Since the 3’end of the adapter is blocked, it can’t serve as a substrate for self-ligation.
The second step of microRNA library preparation involves a 5’RNA adapter which is ligated to the 5’phosphate end of microRNA by T4 RNA Ligase 1. RNA molecules with a 5’phosphate are the only substrates for this ligation reaction. The resultant products are dual and partially ligated small RNA molecules.
The third step of this protocol involves annealing a reverse transcription primer to the 3’ligated adapter and extension. This is followed by PCR amplification using a pair of primers that add on Illumina flow cell binding sequences and barcodes. The final amplified small RNA library consists of approximately 120 bases of adapter sequence plus an insert of between ~22 - 30 bases. Higher molecular weight products are generated from ligation of non-microRNA species, including tRNAs, snoRNAs, piRNAs and other RNA fragments. These can be removed by bead based size selection or PAGE purification. When sequenced, reads are read from the 5’end to the 3’end of the RNA molecule. This general approach can be used for creating directional RNA libraries and is frequently used in RIP and CLIP-Seq applications.
One of the main limitations in small RNA-seq differential expression studies are the ligation biases introduced during the 3’ and 5’ end ligation steps. The first method to identify and remediate these biases was discovered by Jayaprakash et al., 2011. The solution was to add a series of degenerate bases at the 3’ end of the 5’ RNA adapter and 5’ end of the 3’ DNA adapter. The only commercial kit to implement this bias reducing strategy is the NEXTflex Small RNA-Sequencing Kit. Recent work by Baran-Gale et al., 2015 has shown the NEXTflex protocol to be the least biased of all library preparation protocols, resulting in the best differential expression correlation to qPCR.
One of the biggest limitations to the small RNA library protocol are the insert-less 5’adapter and 3’adapter ligations that form what are called adapter dimers. These dimers compete for resources during RT-PCR. When over-amplified, these ~120 bp products can contaminate true 150 bp microRNA library bands. To minimize this effect four main strategies are employed to reduce adapter dimer:
Yes. As of early 2016, there were less than 2000 published human micoRNAs in miRBase, a searchable database of published and annotated miRNA sequences. With sequencing outputs now near 400M per run, it makes sense to multiplex tens to hundreds of microRNA libraries. To determine the level of multiplexing or number of libraries you should pool together, consider whether you’re interested in differential expression, microRNA profiling or discovery of novel/new microRNAs. The latter application, discovery, will require reads between 5-10 million, while profiling studies typically only require 100K – 1M reads per library.
When studying differential expression of both mRNA and small RNAs, two separate library constructions (protocols) must be performed on the same total RNA sample. Frequently, a researcher will hope to sequence both small RNAs and mRNAs in the same library. MicroRNAs have lower expression levels than mRNA and library prep procedures are typically biased toward selecting for either small or large size products, making it an either/or proposition.
Associations between miRNAs and mRNA can be found in databases such as mirWalk and miRBase. Tools such as CORNA, MMIA and MAGIA offer predictions based on associations between genes, miRNAs and relatedness of the gene target and microRNA profile.
Yes, both can be submitted for small RNA library preparation. The miRNeasy™ Mini Kit from Qiagen, mirVana™ from Thermo Fisher, TRIZol with isopropanol, mirPremier™ from Sigma all can be used to isolated small RNA from total RNA or tissue samples. While, small RNA can be selectively purified from total RNA or tissue, we recommend simply isolating total RNA for small RNA-sequencing applications. Small RNA selection methods can introduce bias. All commercial small RNA library preparation kits can use total RNA as input.
Most service providers require at least 500 ng of total RNA or 100 ng of isolated microRNA.
We recommend submitting samples that have an A260/280 ratio greater than 1.6. You can also check the total RNA integrity number (RIN) using a Bioanalyzer. RIN values of 7 or greater are typically sufficient for miRNA library preparation.
After adapter trimming, high quality sequencing reads are typically mapped to a reference genome annotated with miRBase to measure mapping percentages. microRNAs and the number of reads are listed forming the small RNA profile for that particular sample. If the number of reads per sample varies, normalization is applied to offset under-sampling effects.
MicroRNAs are short ~20-30 base RNA species. Only 36 cycles of sequencing is required to capture the entire small RNA sequence. Since 1x36 cycles is not a popular sequencing option, we recommend you sequence your small RNA libraries using a 1x50 or 1x75 bp sequencing run. If you use a run that’s longer, you’ll have to trim the excess cycles before aligning. The Illumina sequence that needs to be trimmed from the 3’end of the reference is:
nnnnnn represents the barcode sequence.
This depends on your application. For expression profiling, 100K–2M mapped reads per sample is generally an accepted range. For discovery applications, 5-10M reads should be considered.